

********************************************************************************
* REPLICATION DO-FILE
* Title: Partners in Government: Politicians' Gender Preferences in Coalition Formation
* Author: Alba Huidobro
* Journal: Political Science Research and Methods
* Date: December 2025
*
* This do-file replicates all figures and tables in the manuscript
********************************************************************************


*******************************
******** SET DIRECTORY ********
*******************************

* Set working directory to current folder (where all data files are located)
* No need to modify this - just make sure all files are in the same folder

	global replication "`c(pwd)'"

	cd "$replication"

* Start logging all output

	capture log close
	log using "replication_log.txt", text replace

* Create folders for outputs

	capture mkdir "figures"
	capture mkdir "tables"

* Set for graphs

	set scheme plotplain

***************************
******** MAIN TEXT ********
***************************

**********************
***** Figure 1 *******
**********************

	use "$replication/data_councillors_aggregated.dta", clear
	
	
	* Figure 1: Women's proportion by position in the city council in Spain from 1979 to 2015
	
	graph twoway (line s_wom_mayor eyear, lpattern(longdash) color(black)) ///
				(line s_wom_deputy eyear, lpattern(solid) color(cranberry)) ///
				(line s_wom_councilor eyear, lpattern(shortdash) color(gs5)), ///
		ytitle("Women proportion") ///
		legend(order(1 "Mayor" 2 "Deputy Mayor" 3 "Councilor") rows(3)) ///
		name(women_position, replace) ///
		xlabel(1979(4)2015) ///
		ylabel(0(0.1).50) title("") 
		
		
	graph export "figures/figure1.pdf", replace

		
**********************
***** Table 2 ********
**********************		
		
		
	*Table 2: Descriptive statistics for the survey respondents vs the whole population

		* NOTE: Table 2 uses individual-level data on mayors (gender, age, education, 
		* party, population, etc.) that cannot be shared due to data protection regulations.
		* The combination of variables would make mayors identifiable.
		
		
**********************
***** Figure 2 *******
**********************

	use "$replication/main_database.dta", clear
	
	

	*Figure 2: Candidate characteristics effects on choosing coalition partners
	

reg person i.gender i.age i.edu i.legis i.ideolog i.seats, vce(cluster id_conjoint)
estimates store general

coefplot 	(general, label(Main results))   ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(small) norecycle ///
			legend(off) level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle() ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(figure2, replace) 
				
		
	graph export "figures/figure2.pdf", replace

		
**********************
***** Figure 3 *******
**********************


	*Figure 3: Candidate characteristics effects on coalition partners assessments


reg polpref i.gender i.age i.edu i.legis i.ideolog i.seats, vce(cluster id_conjoint)
estimates store polpref


coefplot 	(polpref)   ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(small) norecycle ///
			legend(off) level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Similar Political Preferences) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) 

	
	graph export "figures/figure3a.pdf", replace


reg easycomu i.gender i.age i.edu i.legis i.ideolog i.seats, vce(cluster id_conjoint)
estimates store easycomu


coefplot 	(easycomu)   ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(small) norecycle ///
			legend(off) level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Easy Communication) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))
			
			
	graph export "figures/figure3b.pdf", replace

	
reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats, vce(cluster id_conjoint)
estimates store capacity


coefplot 	(capacity)   ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(small) norecycle ///
			legend(off) level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Capacity to govern) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))
			
			
	graph export "figures/figure3c.pdf", replace

	
reg confidence i.gender i.age i.edu i.legis i.ideolog i.seats, vce(cluster id_conjoint)
estimates store confidence


coefplot 	(confidence)   ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(small) norecycle ///
			legend(off) level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Trustworthy) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))
			
			
	graph export "figures/figure3d.pdf", replace

	
	*Table A2. AMCE estimates of Candidates' attributes on profile selection and profile ratings	
	
esttab general polpref easycomu capacity confidence using "tables/tableA2.txt", replace /// 	
	nonumbers nogaps noomit nobase label r2 ///
	scalars("NN Number of Respondents") ///
	cells(b(fmt(%9.3f) star) se(par)) star(* 0.10 ** 0.05 *** 0.01) /// 
	mlabels("Preference" "Similar Political Pref." "Easy Communication" "Capacity to Govern" "Trustworthy") 
	
	
	
	
		
**********************
***** Figure 4 *******
**********************
	
	
	*Figure 4: Assessment effects in choosing potential partners


reg person polpref easycomu confidence capacity, vce(cluster id_conjoint)
estimates store mecha


coefplot 	(mecha, label(Main results))   ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			msize(small) norecycle ///
			legend(off) level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10) subtitle() ///
			ylabel(, labsize(small)) xlabel(-.05(0.05).15, labsize(small)) ///
			name(figure3, replace) 
			
			
	graph export "figures/figure4.pdf", replace
	
	
	*Table A3. Estimates of Assessment effects in choosing potential partners			
	
esttab mecha using "tables/tableA3.txt", replace ///
	nonumbers nogaps noomit nobase label r2 ///
	scalars("NN Number of Respondents") ///
	cells(b(fmt(%9.3f) star) se(par)) star(* 0.10 ** 0.05 *** 0.01) /// 
	mlabels("Preference") 		
		
			

***************************
******** APPENDIX *********
***************************

*********************************************************
* Appendix 1.1 Presence of female politicians in Europe
*********************************************************

	use "$replication/women_mps_world.dta", clear
	
	
	*Figure A1. Share of women in European national parliaments
	
twoway	(line sha_w_mps year if CountryCode=="EUU", lpattern(dash) lwidth(medium) lcolor(gs10))  ///
	(line sha_w_mps year if CountryCode=="ESP", lpattern(solid) lwidth(medthick) lcolor(black)) ///
	(line sha_w_mps year if CountryCode=="DEU", lpattern(shortdash) lwidth(medium))	///
	(line sha_w_mps year if CountryCode=="FRA", lpattern(dash_dot) lwidth(medium))	///
	(line sha_w_mps year if CountryCode=="SWE", lpattern(shortdash_dot) lwidth(medium)) ///
	(line sha_w_mps year if CountryCode=="ITA", lpattern(longdash) lwidth(medium)), ///
	ylabel(0(10)50) ytitle("% of seats of women in national parliaments") xlabel(1997(2)2019) xtitle("") ///
	legend(label(1 "EU28") label(2 "Spain") label(3 "Germany") label(4 "France") label(5 "Sweden") label(6 "Italy") symxsize(*1.5))
	
		
	graph export "figures/figureA1.pdf", replace

	
	*Figure A2. Share of mayors and councilors in European local institutions
	
	use "$replication/women_local_leaders.dta", clear
	
twoway	(line value time if position2==1 & country_code==0, lpattern(dash) lwidth(medium) lcolor(gs10)) ///
	(line value time if position2==1 & country_code==12, lpattern(solid) lwidth(medthick) lcolor(black))  ///
	(line value time if position2==1 & country_code==8, lpattern(shortdash) lwidth(medium)) ///
	(line value time if position2==1 & country_code==14, lpattern(dash_dot) lwidth(medium)) ///
	(line value time if position2==1 & country_code==33, lpattern(shortdash_dot) lwidth(medium)) ///
	(line value time if position2==1 & country_code==19, lpattern(longdash) lwidth(medium)), ///
	ylabel(0(10)50) ytitle("% Female Mayors") xlabel(2011(1)2019) xtitle("") ///
	legend(label(1 "EU28") label(2 "Spain") label(3 "Germany") label(4 "France") label(5 "Sweden") label(6 "Italy") symxsize(*1.5) rows(2) pos(6)) ///
	name(mayors, replace) title("Mayors")

twoway	(line value time if position2==2 & country_code==0, lpattern(dash) lwidth(medium) lcolor(gs10)) ///
	(line value time if position2==2 & country_code==12, lpattern(solid) lwidth(medthick) lcolor(black))  ///
	(line value time if position2==2 & country_code==8, lpattern(shortdash) lwidth(medium)) ///
	(line value time if position2==2 & country_code==14, lpattern(dash_dot) lwidth(medium)) ///
	(line value time if position2==2 & country_code==33, lpattern(shortdash_dot) lwidth(medium)) ///
	(line value time if position2==2 & country_code==19, lpattern(longdash) lwidth(medium)), ///
	ylabel(0(10)50) ytitle("% Female Councilors") xlabel(2011(1)2019) xtitle("") ///
	legend(label(1 "EU28") label(2 "Spain") label(3 "Germany") label(4 "France") label(5 "Sweden") label(6 "Italy") symxsize(*1.5) rows(2) pos(6)) ///
	name(councilors, replace) title("Councilors") 
	

		grc1leg mayors councilors, ycommon ///
		rows(1) position(6) ring(1)graphregion(fcolor(white)) ///
		name(prop_fe_mayorscouncilors, replace) 

	graph export "figures/figureA2.pdf", replace
		

****************************************
* Appendix 3.1 Descriptive information
****************************************			
	
	*Table A1. Characteristics of mayors who answered the survey compared to the whole population
	
		* NOTE: Table A1 uses individual-level data on mayors (gender, age, education, 
		* party, population, etc.) that cannot be shared due to data protection regulations.
		* The combination of variables would make mayors identifiable.

	
********************************************************************************
* Appendix 4.1 Main results of the conjoint experiment for a reduced sample
********************************************************************************

	use "$replication/main_database.dta", clear


preserve 

**Dropping those subjects who spent less time to answer
drop if time_page1_submit<20
drop if time_page2_submit<60 

 
	*Figure A4. Candidate characteristics effects on choosing coalition partners for a reduced sample of mayors


reg person i.gender i.age i.edu i.legis i.ideolog i.seats, vce(cluster id_conjoint)
estimates store general

coefplot 	(general, label(Main results))   ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(small) norecycle ///
			legend(off) level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle() ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(figure2, replace) 
				
	graph export "figures/figureA4.pdf", replace

	
	*Figure A5. Candidate characteristics effects on coalition partners assessments for a reduced sample of mayors


reg polpref i.gender i.age i.edu i.legis i.ideolog i.seats, vce(cluster id_conjoint)
estimates store polpref


coefplot 	(polpref)   ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(small) norecycle ///
			legend(off) level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Similar Political Preferences) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(, replace) 

	graph export "figures/figureA5a.pdf", replace


reg easycomu i.gender i.age i.edu i.legis i.ideolog i.seats, vce(cluster id_conjoint)
estimates store easycomu


coefplot 	(easycomu)   ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(small) norecycle ///
			legend(off) level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Easy Communication) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))

	graph export "figures/figureA5b.pdf", replace


reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats, vce(cluster id_conjoint)
estimates store capacity


coefplot 	(capacity)   ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(small) norecycle ///
			legend(off) level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Capacity to govern) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))

	graph export "figures/figureA5c.pdf", replace

			
			
reg confidence i.gender i.age i.edu i.legis i.ideolog i.seats, vce(cluster id_conjoint)
estimates store confidence


coefplot 	(confidence)   ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(small) norecycle ///
			legend(off) level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Trustworthy) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))

	graph export "figures/figureA5d.pdf", replace


esttab general polpref easycomu capacity confidence, replace /// 	
	nonumbers nogaps noomit nobase label r2 ///
	scalars("NN Number of Respondents") ///
	cells(b(fmt(%9.3f) star) se(par)) star(* 0.10 ** 0.05 *** 0.01) /// 
	mlabels("Preference" "Similar Political Pref." "Easy Communication" "Capacity to Govern" "Trustworthy") 
		
	
		
	
	*Figure A6. Assessment effects in choosing potential partners for a reduced sample of mayors
	
	
reg person polpref easycomu confidence capacity, vce(cluster id_conjoint)
estimates store mecha


coefplot 	(mecha, label(Main results))   ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			msize(small) norecycle ///
			legend(off) level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10) subtitle() ///
			ylabel(, labsize(small)) xlabel(-.05(0.05).15, labsize(small)) ///
			name(figure3, replace) 

	graph export "figures/figureA6.pdf", replace

					
	
esttab mecha, replace /// 	
	nonumbers nogaps noomit nobase label r2 ///
	scalars("NN Number of Respondents") ///
	cells(b(fmt(%9.3f) star) se(par)) star(* 0.10 ** 0.05 *** 0.01) /// 
	mlabels("Preference") 		
		
		
	
restore 

	
	
********************************************************************************
* Appendix 4.2 Heterogeneous Treatment Effects by Mayors Characteristics
********************************************************************************	


	*Figure A7. Candidate characteristics effects on choosing coalition partners by respondents' characteristics

	
reg person i.gender i.age i.edu i.legis i.ideolog i.seats if genderresp==0, vce(cluster id_conjoint)
estimates store men

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if genderresp==1, vce(cluster id_conjoint)
estimates store women



coefplot 	(men, label(Men) offset(0.2)) ///
			(women, label(Women) offset(-0.2)) /// 
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Gender) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A7a, replace)
			

	graph export "figures/figureA7a.pdf", replace


				
reg person i.gender i.age i.edu i.legis i.ideolog i.seats if ageresp_g==0, vce(cluster id_conjoint)
estimates store young

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if ageresp_g==1, vce(cluster id_conjoint)
estimates store old


coefplot 	(young, label(Under 50) offset(0.2)) ///
			(old, label(Over 50) offset(-0.2)) /// 
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Age) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))  ///
			name(A7b, replace) 
			
	graph export "figures/figureA7b.pdf", replace
					

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if edurespondent==1, vce(cluster id_conjoint)
estimates store low

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if edurespondent==2, vce(cluster id_conjoint)
estimates store med

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if edurespondent==3 | edurespondent==4, vce(cluster id_conjoint)
estimates store high


coefplot 	(low, label(Primary) offset(0.3)) ///
			(med, label(Secondary)) /// 
			(high, label(University) offset(-0.3))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Education) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))  ///
			name(A7c, replace) 
			
	graph export "figures/figureA7c.pdf", replace

			
reg person i.gender i.age i.edu i.legis i.ideolog i.seats if ideolresp_g==1,vce(cluster id_conjoint)
estimates store left

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if ideolresp_g==2,vce(cluster id_conjoint)
estimates store center

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if ideolresp_g==3, vce(cluster id_conjoint)
estimates store right


coefplot 	(left, label(Left) offset(0.3)) ///
			(center, label(Center)) /// 
			(right, label(Right) offset(-0.3))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Ideology) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))  ///
			name(A7d, replace) 
			
	graph export "figures/figureA7d.pdf", replace
			

		
			*Figure A8. Evaluation on similar political preferences by respondents' characteristics
				

reg polpref i.gender i.age i.edu i.legis i.ideolog i.seats if genderresp==0, vce(cluster id_conjoint)
estimates store polpref_men

reg polpref i.gender i.age i.edu i.legis i.ideolog i.seats if genderresp==1, vce(cluster id_conjoint)
estimates store polpref_women

coefplot 	(polpref_men, label(Men) offset(0.2)) ///
			(polpref_women, label(Women) offset(-0.2)) /// 
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Gender) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A8a, replace) 
			
	graph export "figures/figureA8a.pdf", replace

			
reg polpref i.gender i.age i.edu i.legis i.ideolog i.seats if ageresp_g==0, vce(cluster id_conjoint)
estimates store polpref_young

reg polpref i.gender i.age i.edu i.legis i.ideolog i.seats if ageresp_g==1, vce(cluster id_conjoint)
estimates store polpref_old

coefplot 	(polpref_young, label(Under 50) offset(0.2)) ///
			(polpref_old, label(Over 50) offset(-0.2)) /// 
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Age) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A8b, replace) 
			
	graph export "figures/figureA8b.pdf", replace
			

reg polpref i.gender i.age i.edu i.legis i.ideolog i.seats if edurespondent==1, vce(cluster id_conjoint)
estimates store polpref_low

reg polpref i.gender i.age i.edu i.legis i.ideolog i.seats if edurespondent==2, vce(cluster id_conjoint)
estimates store polpref_med

reg polpref i.gender i.age i.edu i.legis i.ideolog i.seats if edurespondent==3 | edurespondent==4, vce(cluster id_conjoint)
estimates store polpref_high

coefplot 	(polpref_low, label(Primary) offset(0.3)) ///
			(polpref_med, label(Secondary)) /// 
			(polpref_high, label(University) offset(-0.3))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Education) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A8c, replace) 
			
	graph export "figures/figureA8c.pdf", replace
			


reg polpref i.gender i.age i.edu i.legis i.ideolog i.seats if ideolresp_g==1,vce(cluster id_conjoint)
estimates store polpref_left

reg polpref i.gender i.age i.edu i.legis i.ideolog i.seats if ideolresp_g==2,vce(cluster id_conjoint)
estimates store polpref_center

reg polpref i.gender i.age i.edu i.legis i.ideolog i.seats if ideolresp_g==3, vce(cluster id_conjoint)
estimates store polpref_right

coefplot 	(polpref_left, label(Left) offset(0.3)) ///
			(polpref_center, label(Center)) /// 
			(polpref_right, label(Right) offset(-0.3))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Ideology) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A8d, replace) 
						
	graph export "figures/figureA8d.pdf", replace
			
			
			
			*Figure A9. Evaluation on easy communication by respondents' characteristics
			
			
reg easycomu i.gender i.age i.edu i.legis i.ideolog i.seats if genderresp==0, vce(cluster id_conjoint)
estimates store easycomu_men

reg easycomu i.gender i.age i.edu i.legis i.ideolog i.seats if genderresp==1, vce(cluster id_conjoint)
estimates store easycomu_women


coefplot 	(easycomu_men, label(Men) offset(0.2)) ///
			(easycomu_women, label(Women) offset(-0.2)) /// 
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Gender) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A9a, replace) 
			
	graph export "figures/figureA9a.pdf", replace
			
			
reg easycomu i.gender i.age i.edu i.legis i.ideolog i.seats if ageresp_g==0, vce(cluster id_conjoint)
estimates store easycomu_young

reg easycomu i.gender i.age i.edu i.legis i.ideolog i.seats if ageresp_g==1, vce(cluster id_conjoint)
estimates store easycomu_old


coefplot 	(easycomu_young, label(Under 50) offset(0.2)) ///
			(easycomu_old, label(Over 50) offset(-0.2)) /// 
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Age) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A9b, replace) 
			
	graph export "figures/figureA9b.pdf", replace

	
reg easycomu i.gender i.age i.edu i.legis i.ideolog i.seats if edurespondent==1, vce(cluster id_conjoint)
estimates store easycomu_low

reg easycomu i.gender i.age i.edu i.legis i.ideolog i.seats if edurespondent==2, vce(cluster id_conjoint)
estimates store easycomu_med

reg easycomu i.gender i.age i.edu i.legis i.ideolog i.seats if edurespondent==3 | edurespondent==4, vce(cluster id_conjoint)
estimates store easycomu_high

coefplot 	(easycomu_low, label(Primary) offset(0.3)) ///
			(easycomu_med, label(Secondary)) /// 
			(easycomu_high, label(University) offset(-0.3))  ///	
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Education) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A9c, replace) 
			
	graph export "figures/figureA9c.pdf", replace
			
			
reg easycomu i.gender i.age i.edu i.legis i.ideolog i.seats if ideolresp_g==1,vce(cluster id_conjoint)
estimates store easycomu_left

reg easycomu i.gender i.age i.edu i.legis i.ideolog i.seats if ideolresp_g==2,vce(cluster id_conjoint)
estimates store easycomu_center

reg easycomu i.gender i.age i.edu i.legis i.ideolog i.seats if ideolresp_g==3, vce(cluster id_conjoint)
estimates store easycomu_right

coefplot 	(easycomu_left, label(Left) offset(0.3)) ///
			(easycomu_center, label(Center)) /// 
			(easycomu_right, label(Right) offset(-0.3))  ///	
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Ideology) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A9d, replace) 
			
			
	graph export "figures/figureA9d.pdf", replace

			
			
	*Figure A10. Evaluation on capacity to govern by respondents' characteristics
	
	
	
reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats if genderresp==0, vce(cluster id_conjoint)
estimates store capa_men

reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats if genderresp==1, vce(cluster id_conjoint)
estimates store capa_women


coefplot 	(capa_men, label(Men) offset(0.2)) ///
			(capa_women, label(Women) offset(-0.2)) /// 
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Gender) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A10a, replace) 
			
	graph export "figures/figureA10a.pdf", replace
			
			
reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats if ageresp_g==0, vce(cluster id_conjoint)
estimates store capa_young

reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats if ageresp_g==1, vce(cluster id_conjoint)
estimates store capa_old


coefplot 	(capa_young, label(Under 50) offset(0.2)) ///
			(capa_old, label(Over 50) offset(-0.2)) /// 
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Age) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A10b, replace) 
			
	graph export "figures/figureA10b.pdf", replace
			
				
reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats if edurespondent==1, vce(cluster id_conjoint)
estimates store capa_low

reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats if edurespondent==2, vce(cluster id_conjoint)
estimates store capa_med

reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats if edurespondent==3 | edurespondent==4, vce(cluster id_conjoint)
estimates store capa_high

coefplot 	(capa_low, label(Primary) offset(0.3)) ///
			(capa_med, label(Secondary)) /// 
			(capa_high, label(University) offset(-0.3))  ///	
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Education) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A10c, replace) 
			
	graph export "figures/figureA10c.pdf", replace
			
						
reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats if ideolresp_g==1,vce(cluster id_conjoint)
estimates store capa_left

reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats if ideolresp_g==2,vce(cluster id_conjoint)
estimates store capa_center

reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats if ideolresp_g==3, vce(cluster id_conjoint)
estimates store capa_right

coefplot 	(capa_left, label(Left) offset(0.3)) ///
			(capa_center, label(Center)) /// 
			(capa_right, label(Right) offset(-0.3))  ///	
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Ideology) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A10d, replace) 
			
	graph export "figures/figureA10d.pdf", replace
			
			
	*Figure A11. Evaluation on trustworthiness by respondents' characteristics
	
	
reg confidence i.gender i.age i.edu i.legis i.ideolog i.seats if genderresp==0, vce(cluster id_conjoint)
estimates store confi_men

reg confidence i.gender i.age i.edu i.legis i.ideolog i.seats if genderresp==1, vce(cluster id_conjoint)
estimates store confi_women


coefplot 	(confi_men, label(Men) offset(0.2)) ///
			(confi_women, label(Women) offset(-0.2)) /// 	
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Gender) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A11a, replace) 
			
	graph export "figures/figureA11a.pdf", replace
			
	
reg confidence i.gender i.age i.edu i.legis i.ideolog i.seats if ageresp_g==0, vce(cluster id_conjoint)
estimates store confi_young

reg confidence i.gender i.age i.edu i.legis i.ideolog i.seats if ageresp_g==1, vce(cluster id_conjoint)
estimates store confi_old


coefplot 	(confi_young, label(Under 50) offset(0.2)) ///
			(confi_old, label(Over 50) offset(-0.2)) /// 	
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Age) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A11b, replace) 
			
	graph export "figures/figureA11b.pdf", replace
			
	
reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats if edurespondent==1, vce(cluster id_conjoint)
estimates store capa_low

reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats if edurespondent==2, vce(cluster id_conjoint)
estimates store capa_med

reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats if edurespondent==3 | edurespondent==4, vce(cluster id_conjoint)
estimates store capa_high

coefplot 	(capa_low, label(Primary) offset(0.3)) ///
			(capa_med, label(Secondary)) /// 
			(capa_high, label(University) offset(-0.3))  ///	
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Education) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A11c, replace) 
			
	graph export "figures/figureA11c.pdf", replace
			
	
	
reg confidence i.gender i.age i.edu i.legis i.ideolog i.seats if ideolresp_g==1,vce(cluster id_conjoint)
estimates store confi_left

reg confidence i.gender i.age i.edu i.legis i.ideolog i.seats if ideolresp_g==2,vce(cluster id_conjoint)
estimates store confi_center

reg confidence i.gender i.age i.edu i.legis i.ideolog i.seats if ideolresp_g==3, vce(cluster id_conjoint)
estimates store confi_right

coefplot 	(confi_left, label(Left) offset(0.3)) ///
			(confi_center, label(Center)) /// 
			(confi_right, label(Right) offset(-0.3))  ///			
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Ideology) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A11d, replace) 
			
	graph export "figures/figureA11d.pdf", replace
			
				
	
	
	
	*Figure A12. Candidate characteristics effects on choosing coalition partners by respondents' characteristics	
	
	
reg person polpref easycomu confidence capacity if genderresp==0, vce(cluster id_conjoint)
estimates store mecha_men

reg person polpref easycomu confidence capacity if genderresp==1, vce(cluster id_conjoint)
estimates store mecha_women



coefplot 	(mecha_men, label(Men)) ///
			(mecha_women, label(Women) offset(-0.1)) /// 
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10) subtitle(Gender) ///
			ylabel(, labsize(small)) xlabel(-.05(0.05).15, labsize(small)) ///
			name(A12a, replace) 
			
	graph export "figures/figureA12a.pdf", replace
			
	

reg person polpref easycomu confidence capacity if ageresp_g==0, vce(cluster id_conjoint)
estimates store mecha_young

reg person polpref easycomu confidence capacity if ageresp_g==1, vce(cluster id_conjoint)
estimates store mecha_old



coefplot 	(mecha_young, label(Under 50)) ///
			(mecha_old, label(Over 50) offset(-0.1)) /// 
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10) subtitle(Age) ///
			ylabel(, labsize(small)) xlabel(-.05(0.05).15, labsize(small)) ///
			name(A12b, replace) 
			
	graph export "figures/figureA12b.pdf", replace
			
			
	
reg person polpref easycomu confidence capacity if edurespondent==1, vce(cluster id_conjoint)
estimates store mecha_low

reg person polpref easycomu confidence capacity if edurespondent==2, vce(cluster id_conjoint)
estimates store mecha_med

reg person polpref easycomu confidence capacity if edurespondent==3 | edurespondent==4, vce(cluster id_conjoint)
estimates store mecha_high


coefplot 	(mecha_low, label(Primary) offset(0.1)) ///
			(mecha_med, label(Secondary)) /// 
			(mecha_high, label(University) offset(-0.1))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10) subtitle(Education) ///
			ylabel(, labsize(small)) xlabel(-.05(0.05).15, labsize(small)) ///
			name(A12c, replace) 
			
	graph export "figures/figureA12c.pdf", replace
			
	

reg person polpref easycomu confidence capacity if ideolresp_g==1,vce(cluster id_conjoint)
estimates store mecha_left

reg person polpref easycomu confidence capacity if ideolresp_g==2,vce(cluster id_conjoint)
estimates store mecha_center

reg person polpref easycomu confidence capacity if ideolresp_g==3, vce(cluster id_conjoint)
estimates store mecha_right


coefplot 	(mecha_left, label(Left) offset(0.1)) ///
			(mecha_center, label(Center)) /// 
			(mecha_right, label(Right) offset(-0.1))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10) subtitle(Ideology) ///
			ylabel(, labsize(small)) xlabel(-.05(0.05).15, labsize(small)) ///
			name(A12d, replace) 	
					
	graph export "figures/figureA12d.pdf", replace
			
	
				
********************************************************************************
* Appendix 4.3 Robustness to Additional Mayor Characteristics
********************************************************************************			
			
			
	*Figure A13. Candidate characteristics effects on choosing coalition partners by mayors' seniority
	

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if resp_seniority==0, vce(cluster id_conjoint)
estimates store new

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if resp_seniority==1, vce(cluster id_conjoint)
estimates store senior


coefplot 	(new, label(New) offset(0.2)) ///
			(senior, label(Senior) offset(-0.2)) /// 
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Seniority) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))

			
	graph export "figures/figureA13.pdf", replace
			
			
			
	*Figure A14. Candidate characteristics effects on choosing coalition partners by white- or blue-collar mayors

	
reg person i.gender i.age i.edu i.legis i.ideolog i.seats if resp_whitecollar==0, vce(cluster id_conjoint)
estimates store bluecollar

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if resp_whitecollar==1, vce(cluster id_conjoint)
estimates store whitecollar


coefplot 	(bluecollar, label(White collar) offset(0.2)) ///
			(whitecollar, label(Blue collar) offset(-0.2))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(White collar vs. Blue collar) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))
			
	graph export "figures/figureA14.pdf", replace
			
	
		
	*Figure A15. Candidate characteristics effects on choosing coalition partners by dishonest vs. honest politicians
	

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if resp_honesty==1, vce(cluster id_conjoint)
estimates store dishonest

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if resp_honesty==2, vce(cluster id_conjoint)
estimates store honest




coefplot 	(dishonest, label(Dishonest) offset(0.2)) ///
			(honest, label(Honest) offset(-0.2))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Dishonest vs. Honest) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))
			
			
			
	graph export "figures/figureA15.pdf", replace
			
				
	
	*Figure A16. Candidate characteristics effects on choosing coalition partners by major Spanish parties

		
reg person i.gender i.age i.edu i.legis i.ideolog i.seats if partysimpl==1, vce(cluster id_conjoint)
estimates store PSOE

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if partysimpl==2, vce(cluster id_conjoint)
estimates store PP

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if partysimpl==3, vce(cluster id_conjoint)
estimates store Others

coefplot 	(PSOE, label(PSOE) offset(0.2)) /// 
			(PP, label(PP)) ///
			(Others, label(Others) offset(-0.2))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Parties) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))
			
			
	graph export "figures/figureA16.pdf", replace
			
				


	*Figure A17. Candidate characteristics effects on choosing coalition partners by municipality population
	
	
reg person i.gender i.age i.edu i.legis i.ideolog i.seats if pop_g==1, vce(cluster id_conjoint)
estimates store little

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if pop_g==2 | pop_g==3, vce(cluster id_conjoint)
estimates store medium

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if pop_g==4, vce(cluster id_conjoint)
estimates store large



coefplot 	(little, label(Small (<3,000)) offset(0.2)) ///
			(medium, label(Medium (3,000 - 10,000))) /// 
			(large, label(Large (>10,000)) offset(-0.2))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Population Size) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))
			
			
	graph export "figures/figureA17.pdf", replace
			
				
		
	*Figure A18. Candidate characteristics effects on choosing coalition partners by type of government	
	

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if absoluta==0, vce(cluster id_conjoint)
estimates store coalicio

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if absoluta==1, vce(cluster id_conjoint)
estimates store absoluta



coefplot 	(coalicio, label(Minority) offset(0.2)) ///
			(absoluta, label(Absolute Majority) offset(-0.2)) /// 
		, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Type of Government) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))
			
			
	graph export "figures/figureA18.pdf", replace
			
				
			
	*Figure A19. Candidate characteristics effects on choosing coalition partners by citizens' gender attitudes
	

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if femmov==1, vce(cluster id_conjoint)
estimates store mani

reg person i.gender i.age i.edu i.legis i.ideolog i.seats if femmov==0, vce(cluster id_conjoint)
estimates store nomani


coefplot 	(mani, label(Mobilizations) offset(0.2)) ///
			(nomani, label(No Mobilizations) offset(-0.2))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(vsmall) norecycle level(95) ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Gender Attitudes) ///
			ylabel(, labsize(small)) xlabel(, labsize(small))
		
	graph export "figures/figureA19.pdf", replace
			
				
	

********************************************************************************
* Appendix 5. Mechanisms Among Ambitious Mayors	
********************************************************************************	
	
	
	*Figure A20. Candidate characteristics effects on choosing coalition partners by ambitious politicians  
	
	
	reg person i.gender i.age i.edu i.legis i.ideolog i.seats if runagain<=2 & genderresp==0, vce(cluster id_conjoint)
		estimates store ambitious_men
		
	reg person i.gender i.age i.edu i.legis i.ideolog i.seats if runagain<=2 & genderresp==1, vce(cluster id_conjoint)
		estimates store ambitious_women

		coefplot (ambitious_men, label(Ambitious Men) offset(0.2)) ///
			(ambitious_women, label(Ambitious Women) offset(-0.2))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(small) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle() ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) 			
			
	graph export "figures/figureA20.pdf", replace
			
				
		
	*Figure A21. Assessment effects in choosing potential partners by ambitious politicians  
	
	
	reg polpref i.gender i.age i.edu i.legis i.ideolog i.seats if runagain<=2 & genderresp==0, vce(cluster id_conjoint)
		estimates store ambitious_men
		
	reg polpref i.gender i.age i.edu i.legis i.ideolog i.seats if runagain<=2 & genderresp==1, vce(cluster id_conjoint)
		estimates store ambitious_women

		coefplot (ambitious_men, label(Ambitious Men) offset(0.2)) ///
			(ambitious_women, label(Ambitious Women) offset(-0.2))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(small) norecycle ///
			legend(off) level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Similar Political Preferences) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A21a, replace) 
			
	graph export "figures/figureA21a.pdf", replace
			
				
					

	reg easycomu i.gender i.age i.edu i.legis i.ideolog i.seats if runagain<=2 & genderresp==0, vce(cluster id_conjoint)
		estimates store ambitious_men
		
	reg easycomu i.gender i.age i.edu i.legis i.ideolog i.seats if runagain<=2 & genderresp==1, vce(cluster id_conjoint)
		estimates store ambitious_women

		coefplot (ambitious_men, label(Ambitious Men) offset(0.2)) ///
			(ambitious_women, label(Ambitious Women) offset(-0.2))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(small) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Easy Communication) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A21b, replace) 
			
	graph export "figures/figureA21b.pdf", replace
			
				
					

	reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats if runagain<=2 & genderresp==0, vce(cluster id_conjoint)
		estimates store ambitious_men
		
	reg capacity i.gender i.age i.edu i.legis i.ideolog i.seats if runagain<=2 & genderresp==1, vce(cluster id_conjoint)
		estimates store ambitious_women

		coefplot (ambitious_men, label(Ambitious Men) offset(0.2)) ///
			(ambitious_women, label(Ambitious Women) offset(-0.2))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(small) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Capacity to govern) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A21c, replace) 
			
	graph export "figures/figureA21c.pdf", replace
			
				
					
			
			

	reg confidence i.gender i.age i.edu i.legis i.ideolog i.seats if runagain<=2 & genderresp==0, vce(cluster id_conjoint)
		estimates store ambitious_men
		
	reg confidence i.gender i.age i.edu i.legis i.ideolog i.seats if runagain<=2 & genderresp==1, vce(cluster id_conjoint)
		estimates store ambitious_women

		coefplot (ambitious_men, label(Ambitious Men) offset(0.2)) ///
			(ambitious_women, label(Ambitious Women) offset(-0.2))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			headings(	1.gender = "{bf:Gender}" ///
						1.age = "{bf:Age}" ///
						1.edu = "{bf:Education}" ///
						1.legis = "{bf:Terms}" ///
						1.ideolog = "{bf:Ideology}" ///
						1.seats = "{bf:Seats}" ///
						, gap(0.4) labcolor(cranberry) labsize(small)) 	///
			msize(small) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10)  subtitle(Trustworthy) ///
			ylabel(, labsize(small)) xlabel(, labsize(small)) ///
			name(A21d, replace) 
			
	graph export "figures/figureA21d.pdf", replace
			
				

	
	*Figure A22. Candidate characteristics effects on coalition partners assessments by ambitious politicians  


	reg person polpref easycomu confidence capacity if runagain<=2 & genderresp==0, vce(cluster id_conjoint)
		estimates store ambitious_men
		
	reg person polpref easycomu confidence capacity if runagain<=2 & genderresp==1, vce(cluster id_conjoint)
		estimates store ambitious_women

		coefplot (ambitious_men, label(Ambitious Men)) ///
			(ambitious_women, label(Ambitious Women) offset(-0.2))  ///
			, drop(_cons) xline(0, lcolor(gs10)) base  ///
			msize(small) norecycle ///
			legend(rows(1) pos(6) colfirst region(lwidth(none)) size(small) rowgap(minuscule) bmargin(minuscule) ) ///		
			level(95 90) ///
			plotregion(margin(vsmall)) plotregion(margin(none)) ///
			ysize(13) xsize(10) subtitle() ///
			ylabel(, labsize(small)) xlabel(-.05(0.05).15, labsize(small)) 
			
			
	graph export "figures/figureA22.pdf", replace
			
				
			
* Close the log
log close			
			
			
			
			
			
			
			
		